


import logging
import os
from logging import (
    CRITICAL,  # NOQA
    DEBUG,  # NOQA
    ERROR,  # NOQA
    FATAL,  # NOQA
    INFO,  # NOQA
    NOTSET,  # NOQA
    WARN,  # NOQA
    WARNING,  # NOQA
)
from typing import Optional

from tqdm import auto as tqdm_lib


_snake_case	:						Dict         =							{
    '''debug''': logging.DEBUG,
    '''info''': logging.INFO,
    '''warning''': logging.WARNING,
    '''error''': logging.ERROR,
    '''critical''': logging.CRITICAL,
}

_snake_case	:						int         =							logging.WARNING







def 							lowerCAmelCase_	(   ):
							__snake_case						:     str									=  os.getenv("DATASETS_VERBOSITY"				,      _A      )
							if env_level_str:
														if env_level_str in log_levels:
																					return log_levels[env_level_str]
														else:
																					logging.getLogger().warning(
																					    F'Unknown option DATASETS_VERBOSITY={env_level_str}, '
																					    F'has to be one of: { ", ".join(log_levels.keys()      ) }'      )
							return _default_log_level







def 							lowerCAmelCase_	(   ):
							return __name__.split("."      )[0]







def 							lowerCAmelCase_	(   ):
							return logging.getLogger(_get_library_name()      )







def 							lowerCAmelCase_	(   ):
							__snake_case						:     Dict									=  _get_library_root_logger()
							library_root_logger.setLevel(_get_default_logging_level()      )







def 							lowerCAmelCase_	(   ):
							__snake_case						:     Any									=  _get_library_root_logger()
							library_root_logger.setLevel(logging.NOTSET      )







def 							lowerCAmelCase_	(   __lowerCamelCase = None      ):

							if name is None:
														__snake_case						:     Union[str, Any]									=  _get_library_name()
							return logging.getLogger(_A      )







def 							lowerCAmelCase_	(   ):
							return _get_library_root_logger().getEffectiveLevel()







def 							lowerCAmelCase_	(   __lowerCamelCase      ):
							_get_library_root_logger().setLevel(_A      )







def 							lowerCAmelCase_	(   ):
							return set_verbosity(_A      )







def 							lowerCAmelCase_	(   ):
							return set_verbosity(_A      )







def 							lowerCAmelCase_	(   ):
							return set_verbosity(_A      )







def 							lowerCAmelCase_	(   ):
							return set_verbosity(_A      )







def 							lowerCAmelCase_	(   ):
							__snake_case						:     List[str]									=  False







def 							lowerCAmelCase_	(   ):
							__snake_case						:     List[str]									=  True


# Configure the library root logger at the module level (singleton-like)
_configure_library_root_logger()

class 							a						:




							"""simple docstring"""


							def __init__(				self			:    List[Any]       ,      *lowerCamelCase			:    int       ,      **lowerCamelCase			:    Union[str, Any]							)      ->       Union[str, Any]:  # pylint: disable=unused-argument
														__snake_case						:     Union[str, Any]									=  args[0] if args else None

							def __iter__(				self			:    Tuple							)      ->       Dict:
														return iter(self._iterator							)

							def __getattr__(				self			:    Optional[Any]       ,      lowerCamelCase			:    Optional[Any]							)      ->       Any:






														def empty_fn(*lowerCamelCase			:    List[Any]       ,      **lowerCamelCase			:    List[Any]							):  # pylint: disable=unused-argument
																					return

														return empty_fn

							def __enter__(				self			:    Optional[int]							)      ->       Optional[int]:
														return self






							def __exit__(				self			:    Union[str, Any]       ,      lowerCamelCase			:    str       ,      lowerCamelCase			:    List[str]       ,      lowerCamelCase			:    int							)      ->       Union[str, Any]:
														return
_snake_case	:						List[str]         =							True

class 							a						:




							"""simple docstring"""


							def __call__(				self			:    List[Any]       ,      *lowerCamelCase			:    int       ,      lowerCamelCase			:    List[str]=False       ,      **lowerCamelCase			:    List[str]							)      ->       Any:






														if _tqdm_active and not disable:
																					return tqdm_lib.tqdm(*__UpperCamelCase       ,      **__UpperCamelCase							)
														else:
																					return EmptyTqdm(*__UpperCamelCase       ,      **__UpperCamelCase							)

							def        __snake_case   (				self			:    List[str]       ,      *lowerCamelCase			:    Any       ,      **lowerCamelCase			:    str							)      ->       List[str]:
														__snake_case						:     str									=  None
														if _tqdm_active:
																					return tqdm_lib.tqdm.set_lock(*__UpperCamelCase       ,      **__UpperCamelCase							)






							def        __snake_case   (				self			:    Optional[Any]							)      ->       Optional[Any]:






														if _tqdm_active:
																					return tqdm_lib.tqdm.get_lock()
_snake_case	:						str         =							_tqdm_cls()







def 							lowerCAmelCase_	(   ):
							global _tqdm_active
							return bool(_tqdm_active      )







def 							lowerCAmelCase_	(   ):
							global _tqdm_active
							__snake_case						:     Union[str, Any]									=  True







def 							lowerCAmelCase_	(   ):
							global _tqdm_active
							__snake_case						:     Any									=  False



"""simple docstring"""



import importlib

import torch
import yaml
from omegaconf import OmegaConf
from taming.models.vqgan import VQModel


def 			_UpperCamelCase						(    _A       ,   _A=False   )     ->	Optional[Any]:





    """simple docstring"""

    _UpperCAmelCase        = OmegaConf.load(_A   )
    if display:
        print(yaml.dump(OmegaConf.to_container(_A   )   )   )
    return config


def 			_UpperCamelCase						(    _A       ,   _A=None       ,   _A=None   )     ->	List[Any]:





    """simple docstring"""

    if conf_path is None:
        _UpperCAmelCase        = """./model_checkpoints/vqgan_only.yaml"""
    _UpperCAmelCase        = load_config(_A       ,   display=_A   )
    _UpperCAmelCase        = VQModel(**config.model.params   )
    if ckpt_path is None:
        _UpperCAmelCase        = """./model_checkpoints/vqgan_only.pt"""
    _UpperCAmelCase        = torch.load(_A       ,   map_location=_A   )
    if ".ckpt" in ckpt_path:
        _UpperCAmelCase        = sd["""state_dict"""]
    model.load_state_dict(_A       ,   strict=_A   )
    model.to(_A   )
    del sd
    return model


def 			_UpperCamelCase						(    _A       ,   _A   )     ->	Union[str, Any]:





    """simple docstring"""

    _UpperCAmelCase     ,_UpperCAmelCase     ,_UpperCAmelCase        = model.encode(_A   )
    print(F"""VQGAN --- {model.__class__.__name__}: latent shape: {z.shape[2:]}"""   )
    _UpperCAmelCase        = model.decode(_A   )
    return xrec


def 			_UpperCamelCase						(    _A       ,   _A=False   )     ->	Optional[Any]:





    """simple docstring"""

    _UpperCAmelCase     ,_UpperCAmelCase        = string.rsplit("""."""       ,   1   )
    if reload:
        _UpperCAmelCase        = importlib.import_module(_A   )
        importlib.reload(_A   )
    return getattr(importlib.import_module(_A       ,   package=_A   )       ,   cls   )


def 			_UpperCamelCase						(    _A   )     ->	str:





    """simple docstring"""

    if "target" not in config:
        raise KeyError("""Expected key `target` to instantiate."""   )
    return get_obj_from_str(config["""target"""]   )(**config.get("""params"""       ,   {}   )   )


def 			_UpperCamelCase						(    _A       ,   _A       ,   _A=True       ,   _A=True   )     ->	Union[str, Any]:





    """simple docstring"""

    _UpperCAmelCase        = instantiate_from_config(_A   )
    if sd is not None:
        model.load_state_dict(_A   )
    if gpu:
        model.cuda()
    if eval_mode:
        model.eval()
    return {"model": model}







def 			_UpperCamelCase						(    _A       ,   _A       ,   _A       ,   _A   )     ->	Optional[Any]:





    """simple docstring"""

    if ckpt:
        _UpperCAmelCase        = torch.load(_A       ,   map_location="""cpu"""   )
        _UpperCAmelCase        = pl_sd["""global_step"""]
        print(F"""loaded model from global step {global_step}."""   )
    else:
        _UpperCAmelCase        = {"""state_dict""": None}
        _UpperCAmelCase        = None
    _UpperCAmelCase        = load_model_from_config(config.model       ,   pl_sd["""state_dict"""]       ,   gpu=_A       ,   eval_mode=_A   )["""model"""]
    return model, global_step